System and method for using draft position information to aid player selection in a fantasy league draft

ABSTRACT

In a fantasy league draft, prior to a user-participant making a player selection at a given draft position, a programmatic determination is made as to a likelihood that a particular player will be available for selection in one or more subsequent draft positions. The draft positions may be ones assigned to a particular user-participant, or any draft position a user-participant wants to consider. In one embodiment, the determination is then communicated to the user-participant prior to the user-participant making the payer selection in the given draft position

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.11/456,181 entitled “System and Method For Using Draft PositionInformation To Aid Player Selection In A Fantasy League Draft,” filed onJul. 7, 2006, which is a continuation-in-part of U.S. patent applicationSer. No. 10/835,952, entitled “System and Method for FacilitatingAnalysis of Game Simulation of Spectator Sports Leagues,” filed on Apr.30, 2004, and naming Theodore Kasten as sole inventor. Theaforementioned priority applications are hereby incorporated byreference in their entirety.

TECHNICAL FIELD

The disclosed embodiments relate generally to the field of gamesimulations of spectator sports. In particular, the disclosedembodiments relate to a system and method for facilitating gamesimulation of a spectator sport.

BACKGROUND

Spectator sports, such as professional or collegiate football, baseball,basketball, and hockey, rely on fan participation to generate revenueand enthusiasm. Over the years, fan participation and enthusiasm hasdriven spectator sports to become highly lucrative. As a result,numerous secondary businesses and events have been fostered and createdbased on the ever increasing popularity of the spectator sport.

Fantasy leagues, in particular, are an increasingly popular andsophisticated derivative of spectator sports. Currently, fantasy leaguesfor football, baseball, basketball and hockey are readily available. Theemergence of the Internet and online environment has in particularfostered the growth behind the fantasy leagues.

In general, a fantasy league simulates, or at least corresponds, toevents of a particular sports league. Fantasy football leagues, forexample, have members that form fantasy teams. Each fantasy team mayhave designated positions corresponding to what an actual sports teamhas. For example, a fantasy football team may have all the offensive,defensive and special team positions of an actual professional footballteam. The members of a fantasy league go through a selection processwhere each makes a selection of a particular player for his team. Amember of a fantasy football league can fill the positions of hisfantasy team by assigning a particular position or role on his team to anamed football player. The team that the named player plays on in theactual sports league is not relevant in the fantasy team. But thestatistics the named player acquires in the course of a season areconverted into fantasy numbers. The member's fantasy team is then rankedagainst other fantasy teams by an aggregate or total value reflectingthe fantasy numbers of all positions or slots in the fantasy team, whereeach such fantasy number is derived from the performance of acorresponding player in the actual sports league. The fantasy numberthat is determined for a player is usually statistical in nature,reflecting both positive statistics (scoring a touchdown, throwing acompleted pass, running yardage) and negative statistics (fumble,interception, incomplete pass) of the player's performance in theseason.

Fantasy numbers may be formulated based on a particular player'sposition. For example, a quarterback fantasy number may use passattempts, completion ration, touchdown passes, and turnovers asstatistical input in deriving an overall fantasy number. In contrast, afantasy number for a cornerback may be based on the number ofinterceptions and tackles that the particular cornerback player had inthe course of a season.

Fantasy league services, particularly those that operate on theInternet, sometimes provide some predictive valuation of a player forpurpose of guiding members of the fantasy league to select players. Forexample, a fantasy league service may list a number of quarterbacks inthe NFL along with a fantasy number. The fantasy number may be based onthat player's past performance, particularly in respect to how thatplayer's past performance has been valued in terms of that league'spoint scoring system. A participant or member of a fantasy league mayalso subscribe to third party services, review fantasy sports magazines,or other sources of information to obtain statistical information forpredicting the value of a particular player to his fantasy team. Otherservices may quantify statistics in terms of one or more predictivevalue numbers in order to guide their users in selecting players fortheir fantasy teams. Current methodologies to evaluate players based onhistorical statistics are described in more detail below.

There are different types of fantasy leagues, each with different setsof rules. In general, the rules of the fantasy leagues may be based onthe amount of participation the user of the service is expected to havewith the fantasy teams. Some fantasy leagues are for casual users, whileothers are for more sophisticated users who spend considerable more timedeveloping strategy and data. But in most cases, fantasy leagues havetwo stages: (1) player selection, and (2) team management.

In player selection, the members of the fantasy league make playerselections based on predictions of which players are best suited fortheir team. A player from a sporting team is typically only assigned toone fantasy team, so a league member will not get every player he wants.Rather, league members may be required to rank players and have theservice assign players to each member. Alternatively, a live orsimulated draft may be conducted in which each league member makes aselection in a designated draft order. In either case, the fantasyleague members must make some decisions on what players to select andwhen. For example, the member may make a player selection based on whathe hopes that player will produce in terms of fantasy points, and whatplayers other members in the league are expected to select for theirrespective fantasy teams. Current methodologies to assist users inmaking draft decisions are described below.

After player selection, the members manage their teams. Many fantasysports services let members trade players, release players, and acquirenew players as free agents. However, certain league-dependent rules mayapply to these player transactions. For example, the number of trades amember may make may be limited in a season. The number of acquisitionsmay also be constrained by team size. Members may make managementdecisions based on the performance of their fantasy teams. For example,players performing poorly in terms of points may be released andreplaced. A member may prefer another player, in which case a trade maybe worked out amongst two members in a league. Again, the particulartransactions that can be done with a particular fantasy service dependon the rules of that fantasy service.

Fantasy leagues may include play-off and championship rounds, but theserounds may not be based on playoff or championship events in the actualsports league. For example, some fantasy football leagues designate thefirst 12 weeks of the NFL season the regular season, designate weeks13-16 of the NFL's regular season the playoffs, and ignore week 17, whenmany meaningless games are played. Many fantasy leagues end with week16, because the subsequent playoff season only involves a fraction ofthe players in the NFL.

Existing Player Valuation Methods

There are two basic metrics that are normally used to determine a valueassigned to a player for purpose of predicting that player's value in afantasy league. These metrics include performance categories and afantasy league point system. Performance categories include statisticalquantities of a player's past performances. For example, the performanceof individual offensive and defensive players are tracked in multiplecategories (i.e. Touchdowns, Yardage Gained, Receptions, Interceptions,Field Goals) and aggregated over an entire season. Defensive teams as awhole are also tracked in multiple categories (i.e. Touchdowns Against,Yardage Against, Interceptions, Sacks) and aggregated over an entireseason. Each individual fantasy sports league sets a specific pointvalue for each performance category (i.e. 6 points for a Touchdown, 1point for 20 yards gained, 2 points for a reception, 5 points for aField Goal over 50 yards). These two metrics are combined (e.g.multiplied together and summed) to compute an individual players orteams total estimated fantasy point value.

Existing Draft Methods

There are currently two methodologies used during a fantasy sports draftto help users make decisions on what players to select. The firstmethodology, Value Based Drafting (“VBD”), is the most prominent. Thesecond methodology, Dynamic Value Based Drafting (“DVBD”), is a moreadvanced version of VBD but is not widely used because of the complexityof the calculations. VBD provides a relative value of players incomparison to each other based on a fantasy point value metric beforethe draft starts.

VBD is used to determine which players are the most highly valuedrelative to other players at the same position. To determine whichplayer will provide the most relative value, VBD subtracts from allplayers at a position the value of the last starting player at thatposition based on player rankings (i.e. if there are 10 participants ina league that each have to start 2 Running Backs, then the point valueof the 20^(th) most highly ranked Running Back will be subtracted fromthe point value of all other players). This provides a relative value ofall players available in a draft as compared to the worst startingplayer at their same position.

DVBD uses VBD as its basis and also takes into account changes in thesupply of players at each position as the players are drafted. Theadvantage that DVBD provides over VBD is in calculating the relativevalues of players still available as a draft progresses. Instead ofusing the arbitrary value of the last starting player at each positionas a baseline, DVBD uses the value of the players likely to be availablefor the participants' next draft pick. This value is more pertinent asusers typically compare consecutive draft picks with each other moreoften than they compare their current draft pick with the last pick ofthe draft. This value will change as players are selected and as thedraft progresses.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a methodology for enabling a user of a gamesimulation to formulate a predictive valuation of one or more players ina sports league, according to an embodiment.

FIG. 2 illustrates a method in which dynamic player value parameters maybe used to as part of an overall strategy for a fantasy league,according to an embodiment.

FIG. 3 illustrates a player valuation module for determining playervalues in a fantasy league, according to an embodiment.

FIG. 4 illustrates a method in which players may be valued to facilitatea user's selection in a particular draft round, according to anembodiment.

FIG. 5 illustrates various parameters that can be used to value a playerat the draft stage of a fantasy league, according to an embodiment.

FIG. 6 illustrates a method for evaluating various draft considerationsin the course of a fantasy league draft, according to an embodiment.

FIG. 7 illustrates a network architecture for implementation ofembodiments described herein with a fantasy league.

FIG. 8A illustrates an embodiment in which a user-participant isprovided predictive draft position information, under an embodiment ofthe invention.

FIG. 8B illustrates a more detailed embodiment for enabling auser-participant of a fantasy or simulation league to make playerselection decisions during a draft, using predictive draft positioninformation, under one or more embodiments of the invention.

FIG. 9 illustrates an embodiment for a fantasy sports system thatintegrates various functionality and tools described herein, includingthe ability to provide draft position information for players inconnection with other valuation parameters, under one or moreembodiments of the invention.

FIG. 10A and FIG. 10B provide different implementations of how draftposition information may be presented to a user, under one or moreembodiments of the invention

In the drawings, the same reference numbers identify identical orsubstantially similar elements or acts. To easily identify thediscussion of any particular element or act, the most significant digitor digits in a reference number refer to the Figure number in which thatelement is first introduced. Any modifications necessary to the Figurescan be readily made by one skilled in the relevant art based on thedetailed description provided herein.

DETAILED DESCRIPTION

General Overview and Terminology

Embodiments of the invention provide a system, method, and tool toevaluate and analyze players from real-life sports leagues for purposeof selecting players for use in fantasy teams and other gamesimulations.

An embodiment described herein facilitates a game simulation of a seriesof sporting events that occur over a duration of time. In oneembodiment, a plurality of parameters are associated with individualplayers in a series of sporting events. An input may be detected from auser of the game simulation. The input may indicate a preference of theuser for how one or more of the plurality of parameters are to be valuedin relation to one another. An overall value for one or moreparticipants in the game simulation may be indicated, where the overallvalue corresponds to a value of the plurality of parameters and to theinput.

The following acronyms may refer to the following: NFL (NATIONALFOOTBALL LEAGUE), NBA (NATIONAL BASKETBALL ASSOCIATION), NHL (NATIONALHOCKEY LEAGUE), MBL (MAJOR LEAGUE BASEBALL), MAJOR LEAGUE SOCCER (MLS),and NASCAR (NATIONAL ASSOCIATION FOR STOCK CAR AUTO RACING).

The expression “series of sporting events” may refer to a planned seriesof contests for a particular sports league or organization. In the NFL,for example, a regular season (excluding a playoff season or anexhibition season) includes 16 games played over a period of 17 weeks.

A “game simulation” of a sporting event series refers to anyrecreational and predictive analysis of an aspect of a sporting eventseries. Examples of game simulations include fantasy leagues for seasonof the NFL, the NBA, or MBL. A specific aspect of a sporting eventseries may include a particular player in the sporting event. Forexample, the player may be a football Quarterback or Running Back in theNFL.

A player or participant in a sports league may include a football player(NFL), a basketball player (NBA), a baseball player (MBL), or a hockeyplayer (NHL). The concept of a player or participant may be extended toa team and not just to an individual. In the context of auto racing, theparticipant may include a driver, a driving team, and/or a set of racingcars that belong to one team or are associated with one another (e.g.“Team Porsche”).

The expression “strength of schedule” means, for a given participant, adetermination of a competence level of one or more opposing participantsand/or opposing participant teams. Various methodologies may be used todetermine the competence level of the opposition, some of which aredescribed in more detail below. The opposition may be consideredindividually or in aggregate. In football, for example, theparticipant's team may have a strong strength of schedule rating if theparticipant's team plays more than its share of winning teams.

As used herein, the term “simulation” means a statistical simulation, ora simulation that is based at least in part on a statistical simulation.

In an embodiment, a system, method, technique or tool is provided tofacilitate analysis of a game simulation of a series of sporting eventsthat are to occur in an upcoming season. For example, the gamesimulation may be a fantasy league for an upcoming season of aprofessional sports league. An embodiment provides that a plurality ofparameters are associated to each of a plurality of participants in theseries of sporting events. The plurality of parameters may include atleast a performance-based parameter and a non-performance-basedparameter. A user-specific input from a user of the game simulation maybe detected. The input may indicate how one or more of the plurality ofparameters, including the non-performance-based parameter, are to bevalued in relation to one another. An overall value may be indicated forone or more participants in the game simulation that is to a value ofthe plurality of parameters and the input.

The performance parameters may correspond to metrics that represent aquantity (such as a statistic) that is based on achievement of aplayer's performance. For example, in football leagues such as the NFL,performance parameters may correspond to metrics such as number oftouchdowns scored, how many passes were caught or completed, how manyyards were rushed, number of fumbles lost etc. The performanceparameters may also be based on a combination of two or more performanceparameters, such as the Quarter Back Rating. A non-performance parametermay correspond to a measure (such as a likelihood) that may affect agiven player's performance. Examples of non-performance parametersinclude strength of opponents scheduled (such as strength of opponent'sdefense for offensive players, and strength of opponents offense fordefensive players); consistence, and durability. Consistency anddurability may be based on historical data. Consistency may, forexample, measure deviation amongst performance parameters from game togame in past performances of a player, while durability measures thenumber of times a player has been injured, or for how long etc. Otherexamples of non-performance parameters include measurements for weatheror environmental impact. A specify type of non-performance parametersdescribed in detail below are dynamic player value parameters.

According to another embodiment, a predictive value may be determinedfor a given player in a sports league. The predictive value may be basedon one or more individual games that the given player is scheduled toplay or otherwise perform in. The predictive value may be based at leastpartially on an analysis of the given player playing in each of the oneor more individual games. An overall value of the given player may beindicated using the predictive value of that player for the individualgames.

According to other embodiments described herein, players of a spectatorsports league may be evaluated for a draft in a fantasy league. In oneembodiment, an overall value of a player of the sporting league isdetermined based at least in part on a past performance of the player. Agiven participant of the fantasy league may be indicated an adjustmentto the overall value of a particular player in relation to other playersin the sporting league based on another player that the givenparticipant has already selected for the given participant's fantasyteam. In another embodiment, a comparison may be maintained forindividual players of the sports league, where the comparison indicatesa difference in the value of that player with respect to some referencevalue. The reference value may be another player.

Currently, fantasy football (based on the NFL) is the most popular formof game simulation. For this reason, some examples of embodimentsprovided in the specification are explained in the context of football.However, embodiments described herein may be equally applicable to othersports, including baseball, basketball, hockey, soccer, golf, cricket,auto racing, bowling, horse racing, tennis, poker and chess.Furthermore, embodiments described herein may apply to any league ororganization in which sports or played and statistics are maintained,including non-professional sporting events such as collegiate sports orOlympic events.

Embodiments described herein may be implemented as acomputer-implemented method. The term “computer-implemented method”refers a method that has at least some, but not necessarily all of itssteps performed through execution of instructions by one or moreprocessors. Individual steps of a computer-implemented method may beperformed programmatically, meaning a given step may be performedautomatically through the execution of programming code or logic.

Embodiments of the invention may also be implemented over a network,such as in conjunction with a network service that operates a gamesimulation such as a fantasy league.

In addition, embodiments of the invention may be implemented through useof modules that communicate to users through use of a network. Forexample, an embodiment may be implemented as an integrated, additionalor supplemental service with a network operated fantasy league, such asprovided on the YAHOO! Network or CBS SPORTSLINE. Alternatively, anembodiment may be implemented as a stand-alone application which a userof a fantasy league or other game simulation may use to enhance hisperformance. In one implementation, one or more module may be used toevaluate players for a game simulation, and to enable users of the gamesimulation to make draft picks. As used herein, a module includes aprogram, a subroutine, a portion of a program, a software, firmware orhardware component that is capable of performing a set of tasks orfunctions. A module can exist on a hardware component, such as a serveror client, independently of other modules. Alternatively, a module canexist with other modules on the same server or client, or even withinthe same program.

Player Valuation

One application for an embodiment is a system or tool for use with afantasy sports league, such as a fantasy football league for the NFL, ora fantasy baseball league for the MBL. In the context of suchsimulations, embodiments described herein enable a user participating inthe simulation to make more informed and/or strategic decisionsregarding player/participant selection and team management.

A general format for a fantasy league includes (1) a team formationstage that gives a user an opportunity to make his player selections forhis fantasy team, and (2) a team management phase where a user can viewthe performance of his fantasy team and make certain managementdecisions based on the results. The particular management decisions thatare allowed are based on the particular rules of the fantasy league. Thefantasy team may have designated positions similar to the sporting eventthat it simulates. Players are designated to positions in a givenfantasy team irrespective of their actual team assignment in the sportsleague. It is typical for a fantasy football team, for example, to havea quarterback from one NFL team, and a Running Back from another NFLteam. The exact number of positions, including backup positions that areto be assigned to a fantasy team are determined by the rules of theparticular fantasy league.

A fantasy league normally consists of a set number of fantasy teams.Each of the fantasy teams may be controlled by a user (sometimesreferred to as “team owner”). Generally, the number of teams that canparticipate in a league are set by the rules of the fantasy league. Forexample, many leagues set the number of teams per league at 8, 10, 12 or20. Typically, at the start of a league, all the teams are empty. Adraft or player/participant selection stage is performed, where fantasyteam owners make player selections that result in the fantasy teamsbeing populated. There are different draft rules that can be used togovern the draft order amongst the team owners during a player draft. Asimple fantasy league may have users prioritize their list of players,and then randomly distribute players from the real sports league basedon user-selections. When two or more users select the same player, aprocess makes the decision on which user receives the player based onfactors such as a user's priority for that player and randomness. A moresophisticated fantasy league may have a live or simulated draft, whereeach user's take turns making draft selections. In this scenario, thedraft selections are made from an available pool of players. The orderin which the first round and subsequent rounds of the draft areconducted are important to the users, as the draft order is whatdetermines the user's ability to select a particular player.

Embodiments of the invention enable a participant of the game simulationto evaluate real-life players/participants from a spectator sportsleague for purpose of assigning select players to his fantasy team. Whenplayers are selected for the fantasy team, statistical valuescorresponding to the performance of that player in the sports league arevalued in the fantasy team. The performance of the fantasy team is basedon the statistical performance of the real-life players in the sportsleague. An embodiment described herein facilitates the fantasy leagueuser in evaluating players of the sports league using, at least in part,a sophisticated statistical analysis of various factors relating to theplayer's past performance. These factors assist in predicting aparticular player's success on the fantasy team. Through use ofembodiments described herein, a player may use strategic considerationsto assign his own configuration, weighting or valuation of the variousparameters that comprise the player valuation. In addition, events inthe sporting event series, such as the passing of a week in the NFLseason, may be used to update the parameters of the player valuation onan ongoing basis.

According to another embodiment, a system is provided to assist a userin making draft picks during the team formation stage of a fantasyleague. A system such as described takes into account factors such as(i) what draft picks the user will have (given a particular draft order,rounds, and picks per round), (ii) how selection of a particular playerwill compare to another user's selection of another player, (iii)scheduling conflicts and issues that may affect a player's value to auser, and (iv) ramifications of a user passing on a particular player ina round in view of the user's subsequent order of picks.

FIG. 1 illustrates a methodology for enabling a user of a gamesimulation to formulate a predictive valuation of one or more players ina sports league. The predictive valuation is a measure of how aparticular player is expected to do in terms of fantasy points. Theplayer valuation may be utilized to facilitate a decision in a playerselection stage of the fantasy league. Alternatively, the playerselection may be used during the team management stage to facilitate adecision on what player should be selected as a replacement, or made thebasis of a trade. For example, in some fantasy football leagues, a usermay make a “free agent” acquisition from a pool of available players inorder to replace an injured player. A tool or system described under anembodiment enables the user to make a decision of what player in thefree agent pool is best for him, based on statistic analysis that isconfigured to the user's particular strategic considerations.

For illustrative purposes, embodiments described herein make referenceto a fantasy league as a particular example of a game simulation.Because of its overwhelming popularity, examples emphasize fantasyfootball leagues, but it should be apparent that embodiments andexamples described below are equally applicable to other sports andsports leagues, as well as to other forms of game simulations for suchsports.

According to a method such as shown by FIG. 1, a step 110 provides thatone or more parameters for evaluating players in a spectator sportsleague (or other organization or forum) are defined. The parameters maybe selected based on known information about the sports league that issimulated, including, for example, statistical quantities that indicatea player's value, competence, or skill level. The parameters may bedefined by anyone or all of the following: (i) a host or service thatprovides or otherwise operates the game simulation, (ii) a third-partyservice that operates with a particular game simulation to provide theanalysis described herein, (iii) inherently, within a tool that operateson processing resource to compile statistics and other information for agame simulation (see e.g. player valuation module 710), and (iv) by theuser, on the fly and/or in a predetermined fashion.

Fantasy leagues, for example, operate at different levels ofsophistication. An average level of user-participation in an advancedfantasy league may be much greater than that of a more casual league.Specifically, the parameter definitions for an advanced fantasy leaguemay be more sophisticated, numerous and/or involved than the parameterdefinitions of a more casual fantasy league.

One type of parameter that can be identified is a performance parameter.A performance parameter may correspond to any statistical orquantitative category of a player's past performance. For example, inthe sport of football, each position may have different parameters. ForQuarterback, the parameters may include passing yardage, completionrate, the number of interceptions thrown, and the number of touchdownpasses thrown. For a Running Back, the parameters may include rushingyardage, number of attempts, the number of passes caught, passingyardage, number of touchdowns scored, and the number of fumbles. In thesport of baseball, the parameters may correspond to batting average,home runs, extra base hits (doubles, triples), walks, strikeouts, anderrors. For pitchers, the performance parameters may include number ofwins, number of losses, the pitcher's earned run average, the number ofstrikeouts, the number of innings pitched, the number of saves, and thenumber of blown saves. In basketball, the parameters may correspond topoints scored, shooting percentage, assists, rebounds (both offensiveand defensive), turnovers, free throw percentage, and three-pointpercentage. For the sport of hockey, the performance parameters mayinclude goals scored, shots on goal, and penalty minutes. In golf, theprevious scores of a particular golfer may be calculated. Inauto-racing, vehicle speed and lap times of previous races may be usedfor performance parameters. The aforementioned are just a small sampleof all the performance parameters that can be defined to describe theperformance level, skill level, or past results of participants insports leagues and organizations. Types of statistical categories anddefinitions that are considered under embodiments of the invention areprovided in various publications, including for example: Official 2003National Football League Record & Fact Book (Official National FootballLeague Record and Fact Book), and the Sports Illustrated 2004 Almanac;Tuff Stuff's Fantasy Football Guide (2003 edition), and RotoWorld.com'sBaseball Reference Guide (2004 edition). All of the aforementionedpublications are hereby incorporated by reference in their entirety forpurpose of their respective teachings in the definition and use ofstatistical and quantitative parameters (batting average, rushing yards)of professional and other spectator sports leagues.

In addition to performance parameters, an embodiment provides foridentification and use of parameters that consider player values for anupcoming season on a game-by-game basis. This type of parameter istermed a dynamic player value parameter. This class of parameters buildson the current player valuation methodology by adding metrics that moreaccurately predict the true week-to-week value of a player to a fantasysports team. These metrics enable users to account for the dramaticvariation in performance over an entire season. For example, upcomingscheduled games of a team in a real-life sports league may be analyzedfor attributes or factors that indicate a likelihood that a player'svaluation will be more accurately reflected by a consideration ofindividual games in a player's schedule, rather than a predictiveevaluation of how a player will perform over an entire season. In thisway, a dynamic player value parameter may be predictive of a player'svalue to a fantasy team based on a game-by-game analysis of thatplayer's schedule.

One example of a class of dynamic player value parameters is a parameterthat quantifies a strength of opponent's defenses to a particularplayer. Such a parameter can be valued to predictively quantify thestrength of individual opponent's defenses for each player's team in agiven segment of the season. This parameter may be used to evaluate anoffensive player, such as a Running Back or Quarterback. Another exampleof this type of parameter is a strength of opponents' offense, whichpredictively quantifies the strength of individual opponent's defensesfor each player's team in a given segment of the season. This parametermay be useful in evaluating a defensive player, such as a linebacker orsafety. Both of these examples are described in greater detail below.Numerous other examples exist in addition to the examples providedabove. In the sport of baseball, a strength of opponent's pitching forscheduled games may be used to evaluate how likely a player will dobatting in a given stretch of games. In order to evaluate pitches,parameters that evaluate how well that pitcher's opponents hit or howoften they strikeout may be used.

Step 120 provides that a weighting factor for the different parametersis detected or otherwise determined for a user of the fantasy league.The weighting factor may be determined in anyone of a variety of ways.In one embodiment, the weighting factor may be determined directly via auser-input. For example, the user may specify anyone of the followingwhen determining the fantasy player value of an offensive player: (i)maximize the weighting of a parameter value corresponding to thestrength of opponent's defenses; (ii) minimize the weighting or ignorethe parameter value corresponding to the strength of opponent'sdefenses; (iii) formulate the weighting so that it is a bonus or penaltyfor the player based on the value of the parameter. In addition, theweighting may be varied. For example, some parameters may be given moreweight by the user for purpose of selecting players via the draft, whileother parameters are given more weight when selecting players via freeagency.

The weight factor may also be determined indirectly. For example, theuser may submit one or more profile items, which can then be determinedand correlated to a particular profile for the user of the gamesimulation. As another example, the user may be profiled as arisk-taker, in which case the weighting may be biased towards favoringhigh-risk/high yield parameters. Alternatively, the profile items may bedetermined for the user based on the user's behavior. For example, theuser may be classified or profiled by age group or behavior, such as inthe context of online activity.

In step 130, a set of player values are determined for individualplayers in the sports league. The set of player values may correspond toone metric that combines the values of the different defined parameterswith the user-specific weighting factors. Alternatively, the set ofplayer values may be multi-dimensional, in that multiple metrics about aparticular player are separately presented to the user.

In step 140, users are presented with associated sets of parametervalues for selection of their fantasy team. The sets of parameter valuesmay be displayed, or otherwise communicated to the user in order tofacilitate that user in making a player selection. The manner in whichplayer selections are subsequently made depend on the rules of thesimulation.

FIG. 2 illustrates a method in which dynamic player value parameters maybe used as part of an overall strategy for a fantasy league. Anembodiment such as described may enable participants to evaluate playersdifferently for certain games or portions of the season for the sportsleague. Users of a fantasy league may seek to benefit by using astrategy that is skewed to account for seasonal or game performances ofcertain players. For example, an embodiment such as describedfacilitates analysis of players for game simulations that run forindividual games, or portions of the seasons. Alternatively, anembodiment as described in FIG. 2 enables the user of the gamesimulation to strategize player acquisition and management decisionsbased on specific games or time periods in the season. For example,players that tend to start strong and taper may be identified andselected for trade value during the player acquisition trade, forpurpose of being able to trade that player once the season progresses.

Step 210 provides that a portion of the season for the sports league isdesignated. The portion of the season may correspond to a specific game,a specific set of games, or a portion of the season for the sportsleague. A fantasy football league, for example, may operate in five gamesets over the course of a 17 week football season. Alternatively, a userof a fantasy league may decide to look for players that are mostvaluable at the beginning of the season, or at the end of the season.Thus, the designation of the season portion may be set by a duration ofthe fantasy league, or by strategic considerations of the user.

In step 220, dynamic player value parameters are defined that, for agiven player, provide a player value that is based at least in part on avalue of a performance parameter that is more indicative of the value ofthe given player for the season portion, as opposed to the entireseason. For example, the performance parameter value may predict anoverall player value to be disproportionately impacted by the particularseason segment than the season in aggregate.

In step 230, a player valuation for the portion of the season ispresented for a particular user based at least in part on the parametersdefined in step 220. For example, players may be ranked for a particularsegment of the season, such as the very beginning or very end of theseason. Alternatively, different users may be provided differentvaluations, even for the same set of players, based on weighting inputprovided by those users.

Dynamic Player Valuation Examples

The following are examples of dynamic player value parameters, such asdescribed and/or used with embodiments of FIGS. 1 and 2. In anembodiment, the dynamic player values may be used to determine a valueof a particular player to a fantasy league based on a predictivegame-by-game analyses of the upcoming season for that player.

A durability parameter may be defined to correlate to a player'sdurability. A value for a durability parameter may predict or indicatethe likelihood that a player will miss games in a season due to injury.Injuries to players in the sports-league can make a significant impactto a fantasy team's performance. In an embodiment, as player'sdurability parameter is valued based on the average number of games notplayed due to injury during a season. One manner in which durability canbe quantified is normalize the parameter from −1 to 1; with −1representing the least durable players and 1 representing the mostdurable players. This normalized value is multiplied by (i) auser-defined weighting (percent of player value) for player durability(step 120 of FIG. 1) and (ii) the players point value (based on acompilation of other factors, including performance), to arrive at thefinal value for this metric. This final value is added to the fantasypoint value of each player, as determined from performance parametervalues from past performances. The result of this algorithm is toincrease, or reward, the fantasy point value of players that are lesslikely to get injured and decrease, or penalize, the fantasy point valueof players that are more likely to get injured. When configuring thismetric, users are able to select from (i) reward and penalize playersbased on this metric, (ii) only reward players based on this metric(this rewards players with a normalized value greater than zero), or(iii) only penalize players based on this metric (this penalizes playerswith a normalized value less than zero). A durability parameter valuemay be considered in aggregate for all of the season, or be considered afactor for a specific portion of the season. For example, if thedurability parameter predicts a likelihood of injury, the user of thegame simulation may elect to (i) consider the parameter value inaggregate for the entire season, and/or (ii) consider the parametervalue for only a portion of the season where the player is more likelyto be injured (such as at the end of the season). Therefore, if theplayer is injured in the second half of a season, his performance in thefirst half of the season (or conversely in the second half of theseason) disproportionately impacts his aggregate fantasy point value forthe entire season.

A consistency parameter may be defined based on a consistencymeasurement of the player. A value of a consistency parameter maypredict how constant a player's performance in a sports league will varyfrom game to game. Depending on the manner in which a fantasy league,for example, calculates player valuations, consistency may determinewhen one player's overall or aggregate parameter values or not a trueindication of the player's valuation to a particular fantasy team. In anembodiment, a player's consistency is defined as being based on thestandard deviation of their performances over the span of theirprofessional career. These standard deviations are then normalized from−1 to 1; with −1 representing the least consistent players and 1representing the most consistent players. This normalized value ismultiplied by (i) a user-defined weighting (percent of player value) forplayer consistency (step 120) and (ii) the players fantasy point value,to arrive at the final value for this metric. This final value is addedto the fantasy point value for each player (step 130). The result ofthis algorithm is to increase, or reward, the fantasy point value ofplayers that are more consistent with their performance and decrease, orpenalize, the fantasy point value of players that are less consistentwith their performance. A user may enter a negative number for theweighting for player consistency in which case players would be rewardedfor inconsistent performance and penalized for consistent performance.When configuring this metric users are able to select from (i) rewardand penalize players based on this metric, (ii) only reward playersbased on this metric (this rewards players with a normalized valuegreater than zero), or (iii) only penalize players based on this metric(this penalizes players with a normalized value less than zero).

Another parameter may correspond to a strength of opponents defenses.Such a parameter may be applied to offensive football players, such asthe Quarterback, Running Back and Wide Receiver. Each player's team mayhave a schedule that is accessible to the fantasy league member. Theschedule for the team of a particular offensive player may be evaluatedto determine the Strength of Opponents Defenses for a particular game orset of games. Offensive players typically perform better against weakerdefenses and worse against stronger defenses. The Strength of OpponentsDefenses parameter enables a user to easily account for this potentialvariation in performance. The Strength of Opponents Defenses parametermay be determined for individual games or on an aggregate basis for agiven set of games. According to one implementation, the Strength ofOpponents Defenses can be determined for (i) all weeks of the season(can be configured to include or exclude week 17), (ii) the weeks of thefantasy leagues playoffs (can be configured to include any combinationof weeks including week 13 and beyond), and (iii) the first five gamesof the season (this is not configured). The time period used may bebased on the user's wishes, or on rules of the simulation.

All Game Scenario: The total yards-against of each team defense anoffensive player plays against during each week of the fantasy footballseason is aggregated for each player. It should be noted that there aremany metrics to quantify the strength of opponents. In this context, forexample, other metrics for quantifying the strength of opponents includepoints scored against, passing yards thrown against, and rushing yardsgained against. In one embodiment, the aggregate is based on data fromone or more previous years, for each team involved. In anotherembodiment, the aggregate yards-against number is determined for eachteam on an ongoing basis for a current season of the football league.According to one embodiment, the aggregated values are then normalizedfrom −1 to 1; with −1 representing the best grouping of opposingdefenses (least aggregate yards against) and 1 representing the worstgrouping of opposing defenses (most aggregated yards against). Thisnormalized value may be multiplied by (i) a user-defined weighting(percent of player value) for a season segment (see FIG. 2) and (ii) theplayer's fantasy point value as determined by performance parameters andother valuations. The final value may be added to the fantasy pointvalue to derive a new number. The result of such an algorithm is torecognize (i) additional value for offensive players that play againstpoor defenses during a season segment, (ii) a decrease in value foroffensive players that play against good defenses during this seasonsegment. A user may adjust the weight of this parameter favorably orunfavorably based on other considerations. This particular parameter maybe configured by a user in one of the following ways: (i) reward andpenalize players based on this metric, (ii) only reward players based onthis metric (this rewards players with a normalized value greater thanzero), or (iii) only penalize players based on this metric (thispenalizes players with a normalized value less than zero).

Playoff Game Scenario: The total yards-against (or an alternativemetric) of each team defense an offensive player plays against duringeach week of the fantasy football playoffs is aggregated for eachplayer. The aggregated number may be based on the current fantasyfootball season (e.g. the first 12 games of the year). The aggregatedvalues may then be handled in the manner described with the previousscenario—that is they may be normalized from −1 to 1; with −1representing the best grouping of opposing defenses (least aggregateyards-against) and 1 representing the worst grouping of opposingdefenses (most aggregated yards-against). Similar to the previousscenario, the normalized value is multiplied by (i) a user-definedweighting (percent of player value) for this season segment (such asdescribed in the following step and with FIG. 2) and (ii) the player'sfantasy value from the regular fantasy league season. The result is thefinal value metric, which can be used to reward and/or penalize players,as described with the previous scenario.

Season Segment Scenario: Due to strategy or other considerations, a usermay decide to determine the parameters for certain segments of theoverall season. For example, the user may decide to use the first fiveweeks of the football season to develop a fantasy player for a tradewith another player. In such a scenario, the Strength of OpponentsDefenses parameter may be determined for the teams of select players inorder to identify players that are likely to have strong performances inthat season segment.

Another parameter may correspond to strength of opponents offenses. In,for example, the context of football, this parameter may be used toadjust the fantasy point value for defensive players and defensive teamsbased on the strength of their opponents offenses that they play againstduring certain segments of the season. Defensive players and teamdefenses typically perform better against weaker offenses and worseagainst stronger offenses. These metrics enable users to easily accountfor this potential variation in performance. The season segments include(i) all weeks of the season (can be configured to include or excludeweek 17), (ii) the weeks of the fantasy leagues playoffs (can beconfigured to include any combination of weeks including week 13 andbeyond), and (iii) the first five games of the season (this is notconfigured). This parameter may be used similar to Strength of OpponentsDefenses, described above, for the different segments or portions of aseason.

Player Valuation Module

One or more embodiments described herein may be implemented in the formof a module or program. The module may be accessible to users over anetwork, or alternatively in the form of a client application, so as toserve as a tool to facilitate the participants in the fantasy league.FIG. 3 illustrates a player valuation 310 module for determining playervalues in a fantasy league. In an embodiment, the player valuationmodule 310 may operate on one or more computer systems, and includesinstructions executable by one or more processors.

The player valuation module 310 may process different types of data andinformation, combined with user-input, in order to determine a set ofplayer valuations 322. The player valuations 322 may be made availableto all users. However, the player valuations 322 may be configured forindividual users, so that different users of the module receivedifferent player valuations. Alternatively, player valuation module 310may be executed by users individually, so that the payer valuations 322are made available only to the users who use the module.

In an embodiment, player valuation module 310 receives a player list312. The player list 312 may correspond to a complete or partial list ofall players in a particular sports league at a particular time or timeperiod. For example, the player list 312 may correspond to a list ofplayers on each team in the NFL after the preseason is over and all ofthe teams have been set. The player valuation module 310 may processhistorical statistical data 316 on past performances of individuals inthe player list 312. For a quarterback in football, for example, thehistorical statistical data 316 may include anyone or more of thefollowing: quarterback rating, passing yardage, completion rate,yards-per-attempt, interceptions thrown, and touchdowns thrown. Thehistorical statistical data 316 may also include data that is notspecific to a particular player. For example, the won-loss record ofeach team, or aggregate statistics on teams as a whole, may be compiledin order to cross-reference player specific data with the respectiveplayer's team data.

In an embodiment, player valuation module 310 also receives futureupcoming season information 318 for determining values of forwardlooking event specific parameters. In an embodiment, this type of dataincludes data for defining and valuing dynamic player values. This typeof data includes, for example, the schedules of the teams for eachplayer that is in player list 312. The historical statistical data 316and the season information 318 may be gathered from informationresources, including libraries or databases. For example, playervaluation module 310 may operate on a terminal that accesses a library,database, or service over a network in order to gain the historicalstatistical data 316 and season information 318. Alternatively, some orall of the data and information may be received manually, from anoperator of the fantasy league, an operator of the player valuationmodule 310, or from a user in the fantasy league.

According to an embodiment, player valuation module 310 also receivesconfiguration input from user(s) of the fantasy league. An example ofconfiguration input includes weighting input 326 that weights howdifferent items in the historical statistical data 316 and the futureinformation 318 should be valued with respect to one another. In anembodiment, the player valuation module uses the data and information ina manner described with embodiments of either FIG. 1 or FIG. 2. Thus,values parameters reflecting performance of a player and forward-lookingevents are determined based on the data and information. Specificexamples of what can be determined for a particular player in the sportsleague include performance parameters, schedules, and metrics such asstrength of schedule, durability and consistency. The weighting input326 may determine what parameters a user thinks is important for aparticular player or set of players, and how much some parameters shouldbe valued over others. For example, the user may wish to weightdurability to penalize the player value of a player because of theirstrength of schedule is strong. Specific examples of how weighting input326 can be used are described with FIG. 1. Because each user in thefantasy league may have a different set of configuration input, oneembodiment provides that the player valuation module 310 accepts inputfrom different users, and maintains for each user in the fantasy leaguea different set of player valuations 322. Thus, different users in thesports league may have different player valuations for the same playerin the sports league. Since each user of the fantasy league can rely onhis own configuration input, the user is able to skew player valuations322 based on his individual strategy. This compares favorably toexisting fantasy sports leagues, which typically provide the same playervaluation numbers to all the users, so that users make decisions whilebeing presented the same set of data.

In addition to configuration data, player valuation module 310 may useother kinds of data 328. For example, weather information may be enteredas input or accessed automatically by the player valuation module 310.Examples of weather information include historical weather data andforecasts. A user may decide to use weather information, or even toweight it. For example, the user may rely on weather information indeciding whether to select a player who is likely to play in inclementweather for a significant portion of the season. This type of data mayconsider how, for example, certain external factors may influence aparticular class of players. For example, with respect to weather orenvironmental conditions, a Kicker or Running Back in football may havea higher metric, at least for this particular consideration, if thatplayer plays indoor games in winter, or is located in a tropicalclimate. An offensive player on a football team with an indoor stadiumand Astroturf may have a higher consideration than a player who is on ateam that plays outdoors and in the Northeast of the country.

Draft Selection

In many fantasy leagues and other game simulations, the player formationstage serves as a foundation for the user's fantasy season. In mostfantasy leagues, for example, the player formation stage is when theuser forms the basis or core of his team. Even the subsequent ability orneed for the user to make additional player acquisitions depends on thequality of the draft. For example, the user may reduce his need forhaving to waive non-performers in favor of free agents, or enhance hisability to make a trade for another player.

As previously mentioned, the team formation stage is called a draft inmany fantasy leagues. An embodiment such as described in this sectionmay have particular relevance to fantasy leagues in which the draft isconducted round by round, with each round having a particular draftorder determined by rules of that fantasy league. A fantasy leaguegenerally consists of a number of teams in the neighborhood of 8-20(although it is possible to have more or fewer). In more sophisticatedleagues, each team gets one pick in a particular draft round. The orderof selection in each draft round is determined by the fantasy leaguerules. A common way to conduct a draft is to randomly select the firstorder, then reverse that order for the next round, and then reverse itback for the third round until all the player positions in each teamhave been selected. For example, Table-1 is one common example of how adraft order may be carried through several rounds:

TABLE 1 Snake Draft Rule 1^(ST) 2^(ND) 3^(RD) 4^(TH) TEAM ID ROUND ROUNDROUND ROUND A 1 6 (12) 1 (13) 6 (24) B 2 5 (11) 2 (14) 5 (23) C 3 4 (10)3 (15) 4 (22) D 4 3 (9) 4 (16) 3 (21) E 5 2 (8) 5 (17) 2 (20) F 6 1 (7)6 (18) 1 (19)

Table 1 illustrates the snake draft rule where the player who has thefirst pick in the first round gets the last pick in the last round.Numbers inside the parenthesis designate the overall draft pick.Numerous variations to this basic scheme are possible. For example, thesecond and third rounds may have the same draft order.

FIG. 4 illustrates a method in which players may be valued to facilitatea user's selection in a particular draft round. A method such asdescribed by FIG. 4 may be performed by anyone or more of the following:(i) a service that conducts the fantasy league, (ii) a third-partyservice or tool that is available to all users of the fantasy league, or(iii) a personal tool used by one or more users in the leagueindependently of other users.

Step 410 provides that player values are calculated for each player inthe real-life sports league, or at least each player that is likely tobe selected. The player value calculations may be based on differentparameters, and in particular, performance parameters.

In step 420, player rankings are formed that consider select number ofavailable players. An embodiment such as described in FIG. 5 providesthat player rankings at the draft stage consider various parameters andmetrics, with a specific category of parameters that are based on draftconsiderations. The player rankings may be sorted by player position.For example, quarterbacks may be ranked based on their respectiveoverall valuations. According to an embodiment, there may be two or morecomponents to the overall player valuation. One component reflects theplayer's overall value, absent any draft consideration (fantasy pointvalue and dynamic point value in FIG. 5). Another component reflectsdraft considerations (draft value points in FIG. 5). With respect to thefirst component, the overall player valuations may be determined in amanner consistent with embodiments described with FIGS. 1-3.Alternatively, player valuations may be determined using moretraditional fantasy point value systems. With respect to draftconsiderations, an embodiment provides that players valuations take intoaccount whether the player selection will maximize the fantasy teamsoverall performance as compared to other teams in the fantasy league.This decision does not necessarily correspond to selecting the playerwith the highest value or player ranking. Rather, decisions may beimpacted by one or more factors such as (i) comparative value of playersavailable as opposed to other users for use in the fantasy league, (ii)the ability to draft quality players in subsequent draft rounds impactthe decision on draft picks. (iii) schedule conflicts amongst players,and (iv) sports team conflicts. These factors are reviewed in greaterdetail with FIG. 5. After each draft pick, or round, these factors willalso change. Specifically, the factors will change because the pool ofavailable players changes. In many cases, so does the draft order.

In step 430, a draft round is conducted. In the round, each user in theleague may make a selection. In step 435, a determination is made as towhether the draft is over. Once the draft is over, the method iscompleted in step 440. If additional rounds remain, then step 450provides that the parameters categorized as draft considerations areupdated. In an embodiment, the update considers the following for aparticular fantasy team: (i) the pool of available players after oneround in the draft, (ii) the players that are already selected for thatteam; (iii) differences amongst available players; and (iv) changes inthe draft order (see Table 1). The method then returns to step 420.

FIG. 5 is a block diagram that illustrates how players may be valued andselected in a player draft of a fantasy league, under an embodiment. Inparticular, FIG. 5 illustrates draft considerations which may be valuedas parameters in evaluating what player should be selected with aparticular draft pick. In a draft, player valuation may be based onthree general categories: (i) a first category 510 for fantasy points,which uses expected performance parameter values to value a player; (ii)a second category 520 of dynamic player value parameters, based onfuture, game-specific considerations; and (iii) a third category 530 ofdraft value considerations. Each category may comprise differentparameters. User-specified weight parameters may affect how categories,individual components and/or parameters of individual categories arevalued in relation to one another. An embodiment such as shown by FIG. 5enables a user to make a draft pick using considerations provided in allthree categories. This allows the user to properly consider the value ofa candidate draft pick based on past performance of that player,game-specific considerations in the upcoming season, and considerationsfrom the draft itself.

The first category 510 of fantasy points may correspond to standardpoint valuations given to players based on expected performances. Anoverall valuation number or indication may be formed based on one ormore parameters of expected performance. In one embodiment, componentsof this category include categories 512 of performance parameter valuesand a fantasy league point system 514.

The second category 520 includes dynamic player value parameters such asdescribed with FIGS. 1 and 2. These values indicate the value a playerwill bring to a fantasy team when games that the player is scheduled toplay in are considered individually, such as parameters of opponentstrength 522, consistency 524, and durability 526.

The third category 530 includes parameters of draft considerations. Onedraft parameter of the player role 532 pertains to whether a startingposition has been completely filled. In fantasy leagues, the performanceof a backup player is usually devalued in relation to a starter. This isthe case even if the backup player is actually a starter in the sportsleague. This parameter can be used to automatically inform the user whena position on a fantasy team has been filled. The result is that theuser can choose players who will be starters, and can value a starterover a backup, regardless of position. In many fantasy leagues, thedraft is conducted quickly, and each team consists of one participants.A tool that tracks when starter positions have been filled on a team hasvalue in that it affords the user an opportunity to track informationthat affects basic player-selection decisions.

Another draft parameter that can be tracked and maintained as a draftprogresses is a team parameter 534. The team parameter 534 may be valuedto track a degree to which available players are on the same sportsteams. If a fantasy team has too many players on one sports team, theuser may be taking an unplanned risk. For example, an unexpected badseason by that team may detrimentally affect the performance of allplayers on that team.

Both of the role parameter 532 and the team parameter 534 draftparameters provide examples of instances when, as the draft progresses,the user can devalue a particular player because of that user's previousdraft pick. For example, in football, once the fantasy user selects afirst quarterback, a system such as described automatically devaluesremaining quarterbacks, because the other quarterbacks would serve onlybackup roles on the fantasy team (and by most fantasy rules, fantasypoints from backups are not worth as much). As the draft progresses andthe teams fill out, the ability to automatically monitor this aspectbecomes valuable, particularly when users have limited time to make adraft pick. As another example, once a player selects a set number ofplayers from one team, or from an offense or defense of a team, otherplayers that are still in the draft pool may be devalued for thatplayer. Thus, for example, the fantasy points associated or displayedalong with a player may be reduced as a result of the user havingpreviously selected a certain number of players from the same team.

Other types of draft parameters are contemplated. In particular, a VBDparameter 536 and DVBD parameter 538 associate an opportunity cost witha particular draft selection. The VBD parameter 536 may be based on aVBD methodology for each player position. For example, for a draft roundconsisting of six picks, an embodiment provides that all players areranked by position. Each of the top five players in each position arecompared to the sixth best player in that position. This lets user'sdetermine a cost associated with a particular pick. For example, if theplayers at a particular round of the draft have parity, while at anotherposition there is considerable variance in terms of value, a parameterdetermined from the VBD methodology may conclude that there is too muchcost associated with picking up a player in the first position wherethere is parity. The correct decision may be that even though theavailable player at the second position is not as valuable in terms ofpoints relative to the first player, the second player is the betterdraft pick because of the drop-off in quality from one player to thenext at a particular position.

TABLE 2 VBD tally for Quarterback position in fantasy football.VBD_(QB1) VBD_(QB2) VBD_(QB3) VBD_(QB4) PV_(QB1)-PV_(QBn)PV_(QB2)-PV_(QBn) PV_(QB3)-PV_(QBn) PV_(QB4)-PV_(QBn)

TABLE 3 VBD tally for Running Back position in fantasy football.VBD_(RB1) VBD_(RB2) VBD_(RB3) VBD_(RB4) PV_(RB1)-PV_(RBn)PV_(RB2)-PV_(RBn) PV_(RB3)-PV_(RBn) PV_(RB4)-PV_(Rn)

The Table-2 and Table-3 each illustrates one manner in which VBD valuesmay be used, according to an embodiment. QBn and RBn may refer to aQuarterback and Running Back player, each selected for comparisonpurposes with other players of the same position. For example, anoverall point value of a tenth best Quarterback may be QBn. The rankingsof the Quarterback position may follow: QB1, QB2, QB3 . . . QBn; whilethe rankings of the Running Back position may follow: RB1, RB2, RB3 . .. RBn. The following example illustrates use of the VBD parameter. Inthe third round of a fantasy draft, a user may have a choice between thethird best Running Back (RB3) and the second best Quarterback (QB2). Ifthe VBD number between QB2, QB3 or QB4 is about the same, while there isa more drastic drop-off in the VBD value between RB2 and RB3, the usermay elect RB3 as the better draft choice, even if the point value (oralternatively the estimated points that a particular player will bringto a team) for QB2 is better.

According to an embodiment, VBD parameter 536 values may be maintainedby a draft player module that can be operated as a tool by one or moreparticipants of a fantasy league. In addition, an embodiment providesthe VBD methodology may be configured by a particular user on the-fly.For example, the user may make a new selection on who the referenceplayer is. An embodiment also provides that the values that VBDdeterminations are based on are user-configurable, with selection,omission and or weighting of certain parameters such as described inFIGS. 1-3.

Embodiments of the invention also employ the DVBD methodology tomaintain the DVBD parameter 538. As described previously, DVBDmethodology is similar to VBD methodology, but the basis of comparisonamongst players is two consecutively ranked players having the sameposition. Specifically, a tool or system may maintain DVBD values foreach player available in the draft pool. As with VBD parameter 536, theDVBD parameter 538 is intended to determine a cost associated with aparticular pick. However, as explained earlier, the DVBD differs fromthe VBD in that it compares players that are consecutively ranked at thesame position.

TABLE 4 A DVBD matrix. Position DVBD₁ DVBD₂ DVBD_(n+1) SDEV QBPV_(QB1)-PV_(QB2) PV_(QB2)-PV_(QB3) PV_(QBn+1)-PV_(QBn) SD_(QB) RBPV_(RB1)-PV_(RB2) PV_(RB2)-PV_(RB3) PV_(RBn+1)-PV_(RBn) SD_(RB) WRPV_(WR1)-PV_(WR2) PV_(WR2)-PV_(WR3) PV_(WRn+1)-PV_(WRn) SD_(WR) TEPV_(TE1)-PV_(TE2) PV_(TE2)-PV_(TE3) PV_(TEn+1)-PV_(Ten) SD_(TE)

As shown by Table-4, the DVBD parameters may be maintained as a matrixthat is automatically updated after each draft pick. Furthermore, thevalue of the DVBD parameter 538 may be different for each user of thefantasy league, particularly when users have the option to weightparameters one way or the other. For example, if different users havedifferent weighting parameters, point values for different positions maybe different, affecting all columns in the table. An embodiment such asdescribed may provide a data structure such as illustrated by Table-4 toallow users in a fantasy league to plan and strategize draft picks. Onedraft strategy may be to select the best player at the particularposition where the Standard Deviation is the highest. This means thatthere are steeper drop-offs in terms of the point value amongst playersin the same position. As a result, the players who have the next draftpicks may lose more in terms of point value from a player at aparticular position. The net result is that the DVBD helps users devaluefor draft purposes players at the same position where there is parity.

In addition, third category 530 of draft considerations may include aparameter 540 that quantifies scheduling conflicts. The opponentschedule for each player may be evaluated to determine if too manyplayers on the same team have the same days off. In particular, if twoplayers are starters and/or have the same position, their absence in onegame may be more detrimental to a fantasy team than if the players wereabsent on different teams. In particular, NFL teams have one or twobye-weeks per season. A fantasy team may want to avoid using twostarting running backs having the same bye-week. In that case, the costof not having a starter on the bye-week may exceed the cost of losingone of two starters over two games.

Various other metrics may be tracked for purpose of determining draftselections and draft values. For example, one embodiment considers whena player will make a subsequent draft selection. In a round of 10 draftpicks, if a player has to wait 10 picks before the next pick, the metricmay be identified to the user. It is possible for certain metrics toreflect a long wait until the next round. For example, in Table-4,likely players to be selected by other users after the player's turn maybe highlighted. However, if the player has consecutive picks (such asthe 10^(th) and 11^(th) in a round of 10), no such indication may beneeded.

The various categories and parameters described in FIG. 5 may beprovided in the form of one or more modules or programs that users of afantasy league can use in order to improve their performance in afantasy league or other game simulation. For example, a module such asdescribed in FIG. 6 may be made available to users over a network.Alternatively, the module may be made available as a download or clientapplication. For example, a user may carry a draft module thatincorporates features described in FIG. 5 on a personal digitalassistant (PDA) or laptop into a live simulated draft of a fantasyleague.

FIG. 6 illustrates a method for evaluating various draft considerationsin the course of a fantasy league draft. For purpose of illustration, amethod of FIG. 6 is described in the context of the sport of football,and in particular, the NFL.

Step 610 provides that players are sorted by position. For example, thisincludes listing players by offensive position (Quarterback, RunningBack etc.), defensive position (Linebacker, Safety), and special teams(Kicker).

Step 615, the player draft is started. The order of the draft may bebased on any factor, such as randomness. Under typical fantasy leaguerules, one team is given one pick per round.

In step 620, players are ranked by position. In an embodiment, theranking is primarily based on parameters in the first category 510,although embodiments include adjusting valuations based onuser-weighting and dynamic parameters (such as opponent strength). Draftconsiderations from the third category 530 may also be considered invaluing a player.

Step 625 provides that a grouping of players of a given ranking (e.g.ranked 1-10) are compared to a common reference player. This step maycorrespond to determining the VBD parameter 536. For example, the best10 players of a particular position may be compared to the player ranked20^(th).

Step 630 provides that players are compared in position to other rankedplayers. In particular, players are compared to the next lowest playerin the ranking determined in step 620.

In step 635, a determination is made as to whether a user's pick is thatuser's first pick. If there has been a previous pick, then step 640provides that a penalty/award value is associated with each player basedon the user's previous draft pick. These may correspond to a value ofrole parameter 532 (indicating starting positions of a particular playerin the draft pool have been filled) and team parameter 534 (indicatingthat a fantasy team is overly weighed with players from one sportsteam).

If the determination in step 635 is that it is the first draft choice ofthe user, or following step 640, step 645 identifies the user's draftselection. Step 650 determines whether the pick was the last of thedraft has ended, in which case the method ends in step 655. If the draftis ongoing, step 660 provides that the next picks of the draft aremonitored until the particular user is up again in the draft. Then themethod is repeated, from step 620.

Network Architecture for Implementation of Game Simulation

A fantasy league may be implemented through numerous mediums. Animportant aspect of a fantasy league is a centralized location wherefantasy team, scores and other information is maintained. Also, it isimportant for users in the fantasy league to communicate with oneanother or at least with the service on which the fantasy league isbeing run. For this reason, fantasy leagues often involve use ofnetworks, such as the Internet.

FIG. 7 illustrates a network architecture for implementation ofembodiments described herein with a fantasy league, according to anembodiment of the invention. Embodiments of the invention include afantasy sports service that facilitates users of a fantasy sports leaguein strategy and making decisions. Components of the service 700 includea player value module 710 and a draft module 720. The player valuemodule 710 may include valuation methodologies that take into accountdynamic player value parameters, such as described in FIGS. 1-3. Theseparameters include, for example, opponent strength, player durability,and player consistency. The draft module 720 may include methodologiesdescribed in FIGS. 4-6, which facilitate draft selections for a fantasyleague user. The draft module 720 and the player value module 710 mayderive information from a database 705 or other libraries. The database705 be populated with data from various data sources 708 that maintainsports league information, including scheduling information, and playerperformance information.

Various network devices may communicate with service 700 over a datanetwork 702. Examples of network devices include desktop computers 732,laptop computers 734, smart phones 736, and wireless devices (such aspersonal digital assistants) 738. The service 700 may be suited forportable devices so that fantasy users may communicate with service 700even when the fantasy league they participate in calls for in-persondraft sessions. It is also possible for an operator/voice interface 740to provide an interface between service 700 and callers using phones 742over the voice network 704. The network devices 732-738 may communicatewith the service 700 via a graphical user-interface 730.

Alternatives for making service 700 available to users exist. In oneembodiment, a user may download components and data for service 700using a laptop or PDA and carry the service and data to a fantasy leagueparticipation forum. Other stand-alone scenarios implementations may beprovided. In addition, an embodiment may be a combined stand-alone andnetwork operated combination. For example, the user may be able toupdate data (e.g. the latest statistics or formulas) for an otherwisestand-alone application that corresponds to an embodiment describedherein. The service 700 may also be integrated into another service formwhich the fantasy league operates. For example, an Internet fantasyleague may offer service 700 as an analysis tool, at additional cost.

Drafting Players Using Draft Position Information

One or more embodiments provide for assisting a user-participant inmaking a player selection during a fantasy league draft (or other teamformation process of a simulation league). One embodiment provides that,prior to a user-participant making a player selection at a given draftposition during a fantasy league draft, a programmatic determination ismade as to a likelihood that a particular player will be available forselection in one or more subsequent draft positions. The draft positionsmay be ones assigned to a particular user-participant, or any draftposition a user-participant wants to consider. In one embodiment, thedetermination is then communicated to the user-participant prior to theuser-participant making the payer selection in the given draft position.

In embodiments described below, the user-participant corresponds to thefantasy league player or team owner. A player, as provided withembodiments described below, is a player in a sports league, and whoseperformance in the sporting events of that league are valued by afantasy league.

Additionally, with embodiments described below, a draft defines adesignated order where individual user-participants can make selectionsof players. A draft position (sometimes referred to as a draft pick) isa position in the designated order.

In another embodiment, the user-participant is programmatically assistedin making a player selection by being provided information representingan aggregate determination of a draft position of one or more players.In one embodiment, the aggregate determination is based on selections ofplayers made in other fantasy league drafts. For example, previousfantasy league drafts conducted days before may be analyzed to determinean average draft position for a given player.

One or more embodiments provide that in a team formation stage (i.e. theplayer draft), a user-participant is provided information indicating thelikelihood that a particular player will be available for selection at asubsequent time. In one embodiment, the user-participant is provided,prior to making a current player selection or draft pick, informationindicating a likelihood of whether a given player will be available atthe user-participant's next opportunity to select a player.

The following example is illustrative. During a player draft of afantasy league, the user-participant may have multiple draft picks,where each draft pick provides an opportunity for that user-participantto select a player from an available player pool. The player may haveone draft pick per round, unless he makes a trade for more draft picks.Prior to making his first round pick, the player may be providedpredictive information indicating one of his desired players will beavailable in the second round.

FIG. 8A illustrates an embodiment in which a user-participant isprovided draft position information, under an embodiment of theinvention. The draft position information may be predictive information,in that it may indicate whether a given player (when identified by nameor player value or rank), or a class or group of players, will beavailable for selection at different draft positions. In one embodiment,the draft position information is determined from sources that includepast player drafts in other fantasy leagues. In particular, the draftposition information may be determined from past player drafts thatoccurred in the same season. The information may also weighted, in favorof, for example, more recent information. The player drafts that areused as a source of information may be provided from a common host, orbe published information. Alternatively, individual user-participantsmay supply the information, or the information may be read from otherleagues conducted by other hosts.

In step 820, the draft position information is used to determine alikelihood that a given player, or a class of players, will beavailable. As will be described, numerous implementations for utilizingthe draft position information are contemplated. The information may bemade available to user-participants individually, or alternatively, toall user-participants of a fantasy/simulation league at one time. Thedraft position information may be used to provide recommendations andinformation predictive of the available player pool at the time of agiven user-participant's draft positions, or at the time of other draftpositions. In the latter case, the draft position information can beused to assist a user-participant in determining whether to make a tradeto change a player draft position assigned to that user-participant.

FIG. 8B illustrates a more detailed embodiment for enabling auser-participant of a fantasy or simulation league to make playerselection decisions during a draft, using draft position information,under one or more embodiments of the invention.

In a step 850, the given user-participant's draft positions areidentified. The user-participant may manually identify his or her draftpositions, or the information may be determined programmatically fromthe service that conducts the draft.

Before a player selection (i.e. draft pick), one embodiment providesthat in step 860, a pool of available players at that draft position isidentified. For example, a method may start by tracking all players thatcan be drafted in a draft or team formation stage. With each playerselection, the available player pool is updated. When theuser-participant's turn arrives to make a player selection, the pool ofplayers is known for that draft pick.

One embodiment provides that the player values, draft values, andcombinations thereof, are determined for available player's at a givendraft position. Recommendations or quantitative valuations as to whatplayers should be selected by the user-participant at a given draftposition may be made using techniques such as described with FIG. 1-FIG.7. Step 870 may be optional, in that a programmatic guide or tool may beimplemented to provide draft position information independent, orwithout use, of other information for recommending a player draftselection.

In a step 880, draft position information is provided for players or theavailable pool of players. The draft position information may beprovided in various context to aid the user-participant in making aselection. For example, FIG. 10A, and FIG. 10B illustrate differentimplementations for how the draft position information may be used. Inan implementation of FIG. 10A, the draft position information isprovided independently of other information. In an implementation ofFIG. 10B, the draft position information is combined with other valuesto aid the user in making a player selection. As described in, forexample, step 810, various source of information may be used to obtainthe draft position information (other drafts etc.). The draft positioninformation may be integrated with the player an draft values, orprovided separately.

An embodiment such as described with FIG. 8B enables a player to haveupdated information for assisting player selection at each draft pick.Thus, for example, the user-participant can decide whether to make atrade to have a desired draft position that is better or worst thatanother draft position originally assigned to him. For example, theuser-participant may elect to make a trade because his most desiredplayer will most likely not be available at his next opportunity toselect a player.

FIG. 9 illustrates an embodiment for a fantasy sports system thatintegrates various functionality and tools described herein, includingthe ability to provide draft position information for players inconnection with other valuation parameters, under one or moreembodiments of the invention. A system 900 such as shown and describedmay be implemented as part of, for example, a service such as describedwith FIG. 7.

In an embodiment a system 900 includes a player value module 910, adraft value module 920, and a draft position module 930. The playervalue module 910 may provide valuation 912 of players, based ontechniques such as described with other embodiments described herein.Further, as described with one or more embodiments, the draft valuemodule 920 may enhance information provided about a player pool bycomparing players (based on player values) with other available playersin the same position, or with respect to a reference parameter orplayer. Such calculations provide the user-participant an opportunity toview consequences of drafting one player over another. Such draft valueinformation 922 enables the user-participant to evaluate someconsequences of player selections, particularly when players are of acommon class or position. For example, in football, the draft valuemodule 920 may determine that two quarterbacks are available andcomparable in value, while a more measurable difference may existbetween the two best players at a different position.

In an embodiment, the draft position module 930 enhances informationprovided by further providing draft position information 932. Selectioninformation 940 may be provided, for purpose of recommending or aidingthe user-participant in making a player selection, trade or otherdecision. The selection information 940 may present a compilation of theplayer valuations 912, draft value information 922, and draft positioninformation 932. As described with an embodiment of FIG. 8A or FIG. 8B,the draft position information 932 may be predictive, in that pastresults or events on when a given player was selected is communicated tothe user, and the user can infer or anticipate similar results willoccur based in part on the events of the past fantasy league drafts. Forexample, as described with FIG. 10A and FIG. 10B, the information may beprovided in the form of tables.

An embodiment such as described with FIG. 8A, FIG. 8B and FIG. 9 may becombined, or used to enhance, supplement or modify any of theembodiments described with FIG. 1-7 or elsewhere in this application.For example, the draft position information may be combined withparameters that evaluate or otherwise quantify parameters that include(i) a player's overall performance level, based on, for example,historical data; (ii) an estimation of a player's durability orconsistency; (iii) the presence of a scheduling conflict with anotherplayer selected by the user-participant; and (v) strength of schedulefor the player. The draft position information may also be combinedwith, or integrated to enhance, supplement or modify DVBD values, asdescribed with, for example, an embodiment of FIG. 5.

FIG. 10A and FIG. 10B provide different implementations of how draftposition information may be presented to a user, under one or moreembodiments of the invention. In an embodiment, the draft positioninformation is a predictive aid for assisting the user in making aplayer selection during a fantasy league draft.

In a presentation of FIG. 10A, a recommendation table 1010 is providedlisting players by name. The recommendation table 1010 presents a listof players that can be optionally selected by a user-participant at aparticular draft position or time. The recommendation table 1010 may besorted based on different parameters. For example, in FIG. 10A, therecommendation table 1010 lists players by position (running back). Oneof the columns 1016 carries a value 1018 representing anticipated draftposition (“ADP”) information. Specifically, one embodiment provides thatfor each player in the available pool at the start may have associatedwith him (or her) an ADP value that is based on evaluation orobservation of when that player was selected in other fantasy leaguedrafts. As an example, a fantasy draft season may start with severalearly fantasy draft leagues, in anticipation of upcoming season of acorresponding spectator sport. The order of player selections may beobserved or analyzed, and ADP values are determined for use in anothersubsequent fantasy draft league in the same season. As the fantasy draftseason progresses with the numerous leagues (thousands), the ADP valuesare based on a greater number of data points.

In one embodiment, the ADP value 1018 conveys an indication as to where,in the order of all players of a given position (e.g. running back),each player of that position will be taken. Alternatively, therecommendation table 1010 may be sorted by other parameters, includingplayer value or draft values, or a compilation thereof, as discussedwith other embodiments.

FIG. 10B illustrates another recommendation table 1020 in which a set ofplayers are listed and recommended based on a combination of draftposition predictions and draft value determinations. As described withone or more embodiments, the draft value determination represents aplayer valuation (e.g. player value) as compared to the next highestplayer valuation of a player at the same position. From this generalcalculation, an embodiment shown by FIG. 10B supplements the informationby making a determination as to the players that may or are likely to beselected between a given user-participant's current draft position andhis next draft position.

Thus, for example, under one implementation, a program identifies at agiven draft position, (i) a current pool of available players, (ii) theuser-participant's next draft position, and (iii) a hypothetical oranticipated pool of available players at the user-participant's nextdraft position. In one embodiment, the anticipated pool may bedetermined from draft position information of other fantasy leaguedrafts. Specifically, the ADP value of each player may be determinedprior to the draft. If the user-participant's consecutive draftpositions are known (e.g. 3^(rd) and 14^(th) selections in a draft), aprogrammatic means may determine which players have ADP values thatindicate they will be taken before the 14^(th) pick. In this way, theavailable pool may be determined.

In an embodiment shown by FIG. 10B, for each player position, theprogram determines the highest valued player in the current pool (e.g.by player valuation determination of column 1022), and in theanticipated pool (e.g. player valuation determination of column 1024).The difference in player valuations of the two pools is then calculated(value of column 1022 minus value of column 1024). A predictive draftvalue loss is determined in column 1026. This value represents anopportunity cost or lost value of the user-participant in selecting thehighest value player at a given position. For example, in a table ofFIG. 10B, a program would recommend that the user-participant select thehighest ranked wide receiver, even though the quarterback and defensiveplayers that are available at that draft position have much higherplayer valuations. This recommendation predicts that if theuser-participant omits selecting the highest rated player at oneposition (e.g. at quarterback or defensive), the user-participant willhave with his next draft pick, a comparably valued player at each ofthose positions. But, using predictive draft position information todetermine the valuation of the available pool at the user-participant'snext pick, the recommendation is made for the user to select a lowervalued wide receiver, as the wide receiver position holds the biggestpredictive valuation drop-off between the user-participant's draftpicks.

CONCLUSION

The foregoing description of various embodiments of the invention hasbeen presented for purposes of illustration and description. It is notintended to limit the invention to the precise forms disclosed. Manymodifications and equivalent arrangements will be apparent.

1. A computer-implemented method for assisting a user-participant inmaking a player selection during a fantasy league draft, the methodcomprising: prior to the user-participant making a player selection at agiven draft position during a fantasy league draft, making adetermination as to a likelihood that a particular player will beavailable for selection in one or more subsequent draft positions; andcommunicating the determination to the user-participant prior to theuser-participant making the payer selection in the given draft position.2. The method of claim 1, further comprising making the determination asto the likelihood that the particular player will be available forselection at a particular draft position.
 3. The method of claim 2,wherein the particular draft position is the draft position assigned tothe user-participant prior to the user-participant making the selectionin the given round.
 4. The method of claim 1, wherein making adetermination as to a likelihood that a particular player will beavailable is based on information corresponding to a draft position ofthe particular player in one or more other fantasy league drafts.
 5. Themethod of claim 4, wherein the information corresponds to an averagedetermination of the draft position of the particular player in one ormore fantasy league drafts occurring earlier in a same fantasy leagueseason.
 6. The method of claim 1, wherein making a determination as to alikelihood that a particular player will be available is based oninformation corresponding to a draft position of the particular playerin one or more other fantasy league drafts that occur earlier in a samefantasy league season.
 7. The method of claim 1, further comprisingdetermining a value of each player in a plurality of players in a sportsleague that is simulated by the fantasy league draft, wherein the valuefor each player is based at least in part on a past performance of theplayer in the sports league.
 8. The method of claim 7, furthercomprising maintaining a comparison of the value of each player in a setof players, wherein the set of players includes individuals who play inthe sports league at a designated set on one or more positions, andwherein the comparison indicates a difference in the value of eachplayer in the set to a reference value.
 9. The method of claim 8,wherein making a determination as to a likelihood that a particularplayer will be available is based on information corresponding to adraft position of the particular player in one or more other fantasyleague drafts that occur earlier in a same fantasy league season. 10.The method of claim 1, wherein making a determination as to a likelihoodthat a particular player includes making the determination as to thelikelihood that each of a plurality of players will be available forselection in one or more subsequent draft positions.
 11. The method ofclaim 10, wherein communicating the determination to theuser-participant prior to the user-participant making the payerselection includes rendering a table that lists an identifier of eachplayer with information that indicates the likelihood of that playerbeing available with a subsequent draft position of theuser-participant.
 12. A computer-implemented method for assisting auser-participant in making a player selection during a fantasy leaguedraft, the method comprising: prior to the user-participant making aplayer selection at a given draft position during a fantasy leaguedraft, presenting the user-participant with information representing anaggregate determination of a draft position of the one or more players,wherein the aggregate determination is based on selections made in otherfantasy league drafts.
 13. The method of claim 12, further comprisingpresenting the user-participant with the information representing thedraft position that one or more players were selected in other fantasyleague drafts.
 14. The method of claim 12, wherein the informationcorresponds to a value that is based on an average draft position of theeach of the one or more players.
 15. The method of claim 13, whereinpresenting the user-participant with the information representing thedraft position that one or more players were selected in other fantasyleague drafts includes presenting a list of a set of players based on atleast one of (i) a player position, (ii) a player value, or (iii) aplayer draft value.
 16. The method of claim 12, further comprisingperforming at least one of (i) observing the other fantasy league draftsto determine data for determining the information representing theaggregate determination, or (ii) analyzing data from the other fantasyleague drafts to determine the data for determining the information. 17.The method of claim 16, wherein the aggregate information is an average,or a weighted average, of each of the one or more player's draftpositions in a corresponding fantasy league draft occurring in a sameseason.
 18. The method of claim 12, further comprising identifying oneor more subsequent draft positions of the user-participant for selectingplayers after the given draft position, and wherein presenting theuser-participant with information includes presenting the informationbased on the one or more subsequent draft positions of theuser-participant.
 19. The method of claim 12, further comprising rankinga set of available players prior to the user-participant making theplayer selection at the given draft position, wherein ranking the set ofavailable players is based at least in part on the aggregatedetermination of the draft position of at least one of the players inthe set.
 20. The method of claim 19, wherein ranking the set ofavailable players is based at least in part on one or more parametersselected from a group consisting of: (i) a performance based parametercorresponding to an estimation of each player's consistency in pastperformances; (ii) a performance based parameter corresponding to anestimation of each player's durability; (iii) a performance basedparameter corresponding to a performance level of each player; (iv) ascheduling conflict with a player previously selected by theuser-participant; or (v) a strength of each player's opponent for anupcoming season; plurality of performance based parameters on each ofthe players ranked.